BIOENGINEER

Machine Learning Maps Soil Salinity at Depth—and Shows Where Predictions Falter

A study in Shandong Province, China, used quantile regression forests to map soil salinity across five depth intervals down ...

How Do Machine Learning Models Learn? An Overview from Data Preparation to Training, Evaluation, and Prediction

When you start learning machine learning, you encounter many terms such as "features," "loss functions," "gradient descent," ...
BIOENGINEER

Machine learning predicts next-year fitness assessment failure in university students

A longitudinal study at one Chinese university found that annual fitness measurements helped predict subsequent-year ...
Nature

Machine learning articles from across Nature Portfolio

Researchers developed NiCLIP, an AI model that decodes cognitive tasks, concepts, and domains from brain activation patterns. Trained on over 23,000 papers, NiCLIP excels at group-level decoding, ...

Label Design in Financial Machine Learning: Triple Barrier Method, Meta-Labeling, and Pitfalls of Prediction Accuracy

In quantitative trading research, a significant amount of time is spent on model architecture, feature engineering, and ...
Eos

Using Machine Learning Techniques for Polar Vortex Predictions

A new model accurately reproduces aspects of polar vortex behavior, extracting indicators of imminent vortex collapse and accompanying frigid weather in North America and Europe.
Neurology Advisor

Sex-Specific Machine Learning Models Predict 10-Year Dementia Risk

Machine learning models utilizing cardiovascular and lifestyle factors can accurately predict the 10-year risk of dementia in both men and women.
Semiconductor Engineering

How Many Design Experiments Does A Machine Learning Predictor Actually Need?

Machine learning prediction in CAE has a clear proposition: Train a predictor on solved design experiments, then evaluate new designs in seconds instead of hours. The proposition is only as good as ...
Healio

Machine learning deems low-risk extubation failure as high in 18.7% of ventilated patients

Among ventilated adults who underwent extubation, 18.7% were high risk for extubation failure per machine learning even though they met traditional low-risk criteria, according to data presented at ...
Nature

Machine Learning Techniques for Streamflow Forecasting articles from across Nature Portfolio

A precise streamflow forecast is crucial in hydrology for flood alerts, water quantity and quality management, and disaster preparedness. Machine learning (ML) techniques are commonly employed for ...